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cs.CV2025

InstructMoLE: Instruction-Guided Mixture of Low-rank Experts for Multi-Conditional Image Generation

Jinqi Xiao, Qing Yan, Liming Jiang +8

Parameter-Efficient Fine-Tuning of Diffusion Transformers (DiTs) for diverse, multi-conditional tasks often suffers from task interference when using monolithic adapters like LoRA.…

cs.CV2025

Video-As-Prompt: Unified Semantic Control for Video Generation

Yuxuan Bian, Xin Chen, Zenan Li +4

Unified, generalizable semantic control in video generation remains a critical open challenge. Existing methods either introduce artifacts by enforcing inappropriate pixel-wise pri…

cs.CV2025

Lynx: Towards High-Fidelity Personalized Video Generation

Shen Sang, Tiancheng Zhi, Tianpei Gu +2

We present Lynx, a high-fidelity model for personalized video synthesis from a single input image. Built on an open-source Diffusion Transformer (DiT) foundation model, Lynx introd…

cs.CV2024

ID-Patch: Robust ID Association for Group Photo Personalization

Yimeng Zhang, Tiancheng Zhi, Jing Liu +5

The ability to synthesize personalized group photos and specify the positions of each identity offers immense creative potential. While such imagery can be visually appealing, it p…

cs.CV2024

Learning Feature-Preserving Portrait Editing from Generated Pairs

Bowei Chen, Tiancheng Zhi, Peihao Zhu +3

Portrait editing is challenging for existing techniques due to difficulties in preserving subject features like identity. In this paper, we propose a training-based method leveragi…